Channel Estimation and User Localization Assisted by Hybrid RIS with 1-Bit ADCs in MIMO Systems

This paper investigates the deployment of Hybrid Reconfigurable Intelligent Surfaces (HRIS) equipped with analog-to-digital converters (ADCs) with one-bit quantization in multiple-input multiple-output systems to address the inherent limitations of passive elements in traditional RIS. The integration of one-bit ADCs into the HRIS simplifies the system architecture while reducing both cost and energy consumption. For channel estimation and user localization, we jointly leverage the one-bit data received at the HRIS and the reflected signals at the Base Station (BS). The atomic norm minimization method is utilized to substantially enhance the accuracy of channel estimation, while Vandermonde decomposition of a two-level Toeplitz matrix is applied to derive the Angle of Arrival (AoA) information of the User Terminals (UTs). To further optimize the HRIS configuration, we develop a Cramér-Rao Bound-based algorithm. Our simulation results show that the method we propose can improve the performance of both channel estimation and user localization.